Setting design specifications (targets) is a critical task in the early stages of a design process. Flexible targets can accommodate uncertainty and changes in design by postponing design commitments and preserving design freedom. In this work, a new and efficient method for obtaining a ranged set of design specifications that meets the overall design goal while incorporating heterogeneous design capability information is developed. Our proposed method involves two important aspects. First, a quantization algorithm based on rough set theory is used to decompose a design attribute space into subregions based on how well they meet the overall design goal. Second, a new design flexibility measure is used as a metric to select the most desired "target region" based on both the size of the region and the design capability information retrieved from potential design concepts. Our approach captures heterogeneous design capability information in the design attribute space and enhances the ability to adapt to evolving design knowledge as well as unexpected changes. The proposed method is much more efficient than conventional optimization algorithms for solving such problems. The proposed method is demonstrated by a numerical example and the design of a domestic blender.